Microsoft's Decision-1 model enters the fast-growing AI decision model race
Microsoft released Decision-1, a Qwen3.5-9B decision model claiming top accuracy and low latency.
Microsoft launched Decision-1, a decision model based on Qwen3.5-9B for classifications, evaluations, routing, and potentially guiding agents. Microsoft says it led 36 benchmarks covering nearly 150,000 questions, scoring 83.5% accuracy at 85 ms latency and running 2.5 times faster than H2O-Lightning-4B, ahead of Jev 1.13.0. Cloudflare's Qwen-based Clef models were excluded from the comparison. Decision-1 is available on Microsoft Foundry and OpenRouter at $0.042 per million input tokens, with output tokens free.
- Decision-1 is based on Qwen3.5-9B for structured decisions.
- Microsoft reports 83.5% accuracy and 85 ms latency.
- It beat H2O-Lightning-4B on speed by 2.5 times.
- Priced at $0.042 per million input tokens; output is free.
- Available on Microsoft Foundry and OpenRouter.
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Microsoft now has its own decision model. Like the ones from OpenAI, Cloudflare, and the "original" from Jev, Decision-1 is built for fast, structured decisions. According to Microsoft, it handles classifications, evaluations, and routing decisions and has "the potential" to "guide and control agents through complex environments."
Decision-1 is based on Qwen3.5-9B. Microsoft says it's the most accurate model tested across 36 benchmarks covering nearly 150,000 questions. On speed, it's 2.5 times faster than the runner-up, H2O-Lightning-4B. Cloudflare's open-source Clef models, which are also based on Qwen, weren't included in the comparison.
Decision-1 is available through Microsoft Foundry and OpenRouter. Input tokens cost $0.042 per million, and output tokens are free. Jev, the startup that kicked off the decision model trend in mid-September, has likely had a rough few weeks. The idea caught on fast, but the tech was quickly adapted and surpassed using open small language models.
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